Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: receiving an indicator of navigational intent comprising a first navigation event, wherein the first navigation event comprises navigation to a first uniform resource locator selected from a plurality of uniform resource locators; incrementing, with one or more processors and in response to the first uniform resource locator being selected, a first frequency value associated with the first uniform resource locator; conducting, with the one or more processors and in response to the first uniform resource locator being selected, a sweep interval, comprising monitoring navigation during a predetermined amount of time; decaying, with the one or more processors and after the sweep interval, a second frequency value associated with a uniform resource locator from the plurality of uniform resource locators that was not navigated to during the sweep interval; generating a prediction, with the one or more processors, of a second navigation event based at least in part on one or more frequency values associated with one or more of the plurality of uniform resource locators, wherein the second navigation event comprises navigation to a second uniform resource locator; based on the prediction, preemptively retrieving at least a portion of content associated with the second uniform resource locator before a user selects the next navigation event; and displaying the preemptively retrieved content in the event the next navigation event selected by the user corresponds with the second navigation event.
2. The method of claim 1 further comprising, when the second frequency value falls below a given threshold, removing the uniform resource locator associated with the second frequency value from the plurality of uniform resource locators.
3. The method of claim 1 , wherein the decaying includes decaying the second frequency value by a predetermined percentage.
4. The method of claim 1 , wherein the decaying includes decaying the second frequency value by a predetermined value.
This invention relates to signal processing, specifically to methods for adjusting frequency values in a system where signals are analyzed or processed over time. The problem addressed is the need to dynamically modify frequency values to improve signal accuracy, stability, or other performance metrics in applications such as audio processing, communications, or sensor data analysis. The method involves decaying a second frequency value by a predetermined value. This decay process is part of a broader technique where a first frequency value is compared to a second frequency value, and adjustments are made based on their relationship. The decaying step ensures that the second frequency value is systematically reduced by a fixed or predefined amount, which helps stabilize the system or prevent excessive fluctuations. This may be useful in scenarios where gradual adjustments are preferred over abrupt changes, such as in noise reduction, frequency tracking, or adaptive filtering. The predetermined decay value can be a fixed numerical value or a percentage, depending on the application. By applying this decay, the method ensures that the second frequency value converges toward a desired state over time, improving the reliability of the processed signal. This technique is particularly valuable in systems where maintaining consistent frequency behavior is critical, such as in audio equalization, wireless communication protocols, or vibration analysis. The decay mechanism helps mitigate errors or distortions that could arise from sudden frequency shifts, ensuring smoother and more predictable system performance.
5. The method of claim 1 , wherein generating the prediction of the second navigation event is also based on a most visited subsequent uniform resource locator based on a navigation history.
This invention relates to web navigation prediction systems that anticipate a user's next navigation event based on historical browsing patterns. The core problem addressed is improving the accuracy of predicting a user's subsequent web page visit, which is valuable for preloading content, optimizing performance, and enhancing user experience. The method involves analyzing a user's navigation history to identify frequently visited sequences of web pages. Specifically, it generates a prediction for a second navigation event by considering the most visited subsequent uniform resource locator (URL) from the user's past browsing behavior. This means the system tracks which URLs the user most commonly visits after a given page and uses that data to predict the next likely destination. The prediction is not solely based on the current page but also incorporates historical patterns of subsequent visits, improving accuracy over simpler prediction models. The system may also integrate additional factors, such as time-based patterns, session context, or user behavior trends, to refine the prediction. By leveraging historical navigation data, the method aims to reduce latency and improve efficiency in web browsing by preloading or preparing content for the most probable next page. This approach is particularly useful in environments where minimizing load times and optimizing resource usage are critical.
6. The method of claim 5 , further comprising determining if a number of visits to the most visited subsequent uniform resource locator is greater than a threshold number of visits.
7. A system comprising: one or more processors; and memory storing instructions, the instructions being executable by the one or more processors; wherein the instructions comprise: receiving an indicator of navigational intent comprising a first navigation event, wherein the first navigation event comprises navigation to a first uniform resource locator; incrementing in response to the first uniform resource locator being selected, a first frequency value associated with the first uniform resource locator; conducting, in response to the first uniform resource locator being selected, a sweep interval, comprising monitoring navigation during a predetermined amount of time; decaying, after the sweep interval, a second frequency value associated with a uniform resource locator from a plurality of uniform resource locators that was not navigated to during the sweep interval; generating a prediction of a second navigation event based at least in part on one or more frequency values associated with one or more of the plurality of uniform resource locators; based on the prediction, preemptively retrieving content associated with the second navigation event before a user selects the next navigation event; and displaying the preemptively retrieved content in the event the next navigation event selected by the user corresponds with the second navigation event.
8. The system of claim 7 , wherein the instructions further comprise, when the second frequency value falls below a given threshold, removing the uniform resource locator associated with the second frequency value from the plurality of uniform resource locators.
9. The system of claim 7 , wherein the decaying includes decaying the second frequency value by a predetermined percentage.
10. The system of claim 7 , wherein the decaying includes decaying the second frequency value by a predetermined value.
11. The system of claim 7 , wherein generating the prediction of the second navigation event is also based on a most visited subsequent uniform resource locator based on a navigation history.
12. The system of claim 11 , wherein the instructions further comprise determining if a number of visits to the most visited subsequent uniform resource locator is greater than a threshold number of visits.
A system for analyzing web traffic patterns monitors user navigation behavior to identify frequently visited subsequent web pages. The system tracks user interactions with a primary web page and records subsequent web pages accessed after the primary page. It then determines the most frequently visited subsequent web page by counting the number of visits to each subsequent page. The system compares this count against a predefined threshold to assess whether the frequency of visits to the most visited subsequent page exceeds the threshold. This analysis helps identify significant navigation patterns, which can be used for optimizing web page design, improving user experience, or targeting content recommendations. The system may also include additional features such as filtering out certain types of visits or adjusting the threshold dynamically based on historical data. The primary application is in web analytics, where understanding user navigation paths is crucial for enhancing website performance and user engagement.
13. A system comprising: one or more processors; and memory storing instructions, a set of uniform resource locators, and a stored frequency value associated with each uniform resource locator (URL) of the set; wherein the instructions are executable by the one or more processors and comprise: in response to user input selecting a URL by selecting a link on a web page having a plurality of links, incrementing the stored frequency value associated with the selected URL, decaying the stored frequency values associated with each ULR of each link of the plurality the links that is not selected within a predetermined amount of time after the user input selecting the link on the web page, displaying a web page containing at least one link to a URL in the set of uniform resource locators, determining a confidence value for the URL associated with the at least one link, wherein the confidence value is determined based on the stored frequency value associated with the URL, preemptively loading, at least partially and based on the confidence value, content of a web page at the URL associated with the at least one link before the user selects the at least one link, and displaying the web page at the URL associated with the at least one link when the user selects the at least one link.
The system improves web browsing efficiency by predicting and preemptively loading web pages based on user behavior. It tracks user interactions with links on web pages, incrementing a stored frequency value for each selected URL while decaying the values of unselected links over time. This data is used to determine a confidence value for each link, representing the likelihood of user selection. The system then preemptively loads content from high-confidence URLs before the user clicks, reducing perceived latency. The stored frequency values are dynamically adjusted to reflect changing user preferences, ensuring predictions remain accurate. The system operates within a web browser or similar interface, displaying web pages with embedded links and managing the preemptive loading process based on historical interaction data. This approach enhances browsing speed and responsiveness by anticipating user navigation patterns.
14. The system of claim 13 wherein the stored frequency values are based on user input from a plurality of users.
15. The system of claim 13 wherein the web page containing the at least one link to a URL in the set of uniform resource locators further comprises one or more additional links, each link of the one or more additional links being associated with a different URL, wherein the instructions further comprise determining a confidence value for each URL associated with each of the one or more additional links and sorting the confidence values, and wherein loading the content of the web page at the URL associated with the at least one link comprises loading the content of the web page at the URL associated with the at least one link based on the sorted confidence values.
A system for managing web page content loading prioritizes URLs based on confidence values. The system operates in the domain of web browsing and content delivery, addressing the problem of efficiently loading web pages with multiple links to different URLs. The system includes a web page containing at least one link to a URL from a predefined set of URLs. The web page may also include additional links, each pointing to a different URL. The system determines a confidence value for each URL associated with these additional links and sorts these values. When loading the content of the web page at the URL linked by the primary link, the system uses the sorted confidence values to influence the loading process. This ensures that higher-confidence URLs are prioritized, improving the efficiency and relevance of content delivery. The confidence values may be based on factors such as user behavior, historical data, or other relevance metrics, allowing the system to adapt to user preferences and optimize performance. The system dynamically adjusts the loading order of URLs to enhance the browsing experience by reducing latency and improving the relevance of displayed content.
16. The method of claim 1 , wherein generating the prediction of the second navigation event is also based on whether a web page at the first uniform resource locator contains links to one or more of the plurality of uniform resource locators.
17. The system of claim 7 , wherein generating the prediction of the second navigation event is also based on whether a web page at the first uniform resource locator contains links to one or more of the plurality of uniform resource locators.
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January 19, 2021
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